World-centered representation for neural networks

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Abstract

A basic problem for pattern recognition is invariance. This article argues that the traditional full-parallel computation of neural networks that has excluded many useful series computation methods seems improper for the invariance. We introduce a series search mechanism into neural computing. The world-centered recognition is acquired by a pattern-centered memory plus a space search.

Original languageEnglish
Title of host publication1997 IEEE International Conference on Neural Networks, ICNN 1997
Pages597-601A
DOIs
StatePublished - 1997
Event1997 IEEE International Conference on Neural Networks, ICNN 1997 - Houston, TX, United States
Duration: 9 Jun 199712 Jun 1997

Publication series

NameIEEE International Conference on Neural Networks - Conference Proceedings
Volume1
ISSN (Print)1098-7576

Conference

Conference1997 IEEE International Conference on Neural Networks, ICNN 1997
Country/TerritoryUnited States
CityHouston, TX
Period9/06/9712/06/97

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